The UNAM-Droplet Freezing Assay: An Evaluation of the Ice Nucleating Capacity of the Sea-Surface Microlayer and Surface Mixed Layer in Tropical and Subpolar Waters (edited by Dr. Michel Grutter)
Bibliographic record
Abstract
Ice nucleating particles (INPs) in the atmosphere are necessary to generate ice crystals in mixed-phase clouds, a crucial component for precipitation development. The sources and composition of INPs are varied: from mineral dust derived from continental erosion to bioaerosols resulting bubble bursting at the ocean surface. The performance of a home-built droplet freezing assay (DFA) device for quantificatying of the ice nucleating abilities of water samples via immersion freezing has been validated against both published results and analyses of samples from sea surface microlayer (SML) and bulk surface water (BSW) from the Gulf of Mexico (GoM) and Saanich Inlet, off Vancouver Island (VI), Canada. Even in the absence of phytoplankton blooms, all the samples contained ice nucleating particles at moderate concentrations, ranging from 6.0x101 to 1.1x105 L-1 water. The freezing temperatures (i.e., T50, the temperature at which 50% of the droplets freeze) of the samples decreased in order of VI SML > GoM BSW > GoM SML, indicating that the higher-latitude coastal waters have a greater potential to initiate cloud formation and precipitation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".